Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don’t have to manage servers. It also provides common ML algorithms that are optimized to run efficiently against extremely large data in a distributed environment.
SageMaker real-time inference is ideal for workloads that have real-time, interactive, low-latency requirements. With SageMaker real-time inference, you can deploy REST endpoints that are backed by a specific instance type with a certain amount of compute and memory. Deploying a SageMaker real-time endpoint is only the first step in the path to production for many customers. We want to be able to maximize the performance of the endpoint to

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